Automated guided vehicle (AGV) lane-keeping assist based on computer vision, and fuzzy logic control under varying light intensity

Abstract

This paper discusses the development of an automated guided vehicle (AGV) model equipped with a navigation system. The AGV employs computer vision and fuzzy logic control for the lane-keeping assist system as a steering control. The inputs used in fuzzy logic control are the AGV path line gradient values for the left and right lanes. The navigation system uses a camera with a high level of light sensitivity. A light intensity that is too dim or bright will affect the steering control performance, meaning that a certain range of light intensity will affect the performance of the lane-keeping assist. A path with left and right lanes is built to test the performance steering control based on computer vision. The result shows that the optimal light intensity for the developed lane-keeping assists is from 110 to 150 lux. The AGV can successfully follow the path under these light intensities although the deviation still occurs.